Search Results - (( using optimization _ algorithm ) OR ( variable evaluation case algorithm ))
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A MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR WELLBORE TRAJECTORY DESIGN
Published 2021“…To address this issue, a new hybridization of cellular automata (CA) technique with grey wolf optimization (GWO) and particle swarm optimization (PSO) algorithms is proposed in this work which solves these three optimization objectives of drilling through 17 tuning variables. …”
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Development of committee machine models for multiple response optimization problems
Published 2014“…Multiple response optimization (MRO) problems need to optimize several response variables simultaneously. …”
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Optimum MV Feeder Routing and Substation siting and rating in Distribution Network
Published 2014“…The proposed algorithm evaluates on the distribution network case with 164 load blocks. …”
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Optimization Of Fuzzy Logic Controllers With Genetic Algorithm For Two-Part-Type And Re-Entrant Production Systems
Published 2008“…Furthermore, genetic algorithm (GA) has been used to optimize the FLCs performance. …”
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Optimizing n-1 contingency rankings using a nature-inspired modified sine cosine algorithm
Published 2025“…The MSCA method is validated using the IEEE 30-bus test case, focusing on optimal parameter tuning for population size, iterations, and key variables. …”
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Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
“…This study developed an algorithm for statistical classification that enable ones to classify a future data to one of predetermined groups based on the measured data which facing two major threats; (i) multicollinearity among the measured variables and (ii) imbalanced groups. …”
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Optimal placement of unified power flow controller by dynamic implementation of system-variable-based voltage-stability indices to enhance voltage stability
Published 2016“…Furthermore, to verify the suitability of the explored locations, a comparative study has been conducted after placing UPFC in the present locations and other locations obtained using optimization techniques like particle swarm optimization (PSO), differential evolution (DE), genetic algorithm (GA), and bacteria foraging algorithm (BFA). …”
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Development of a two-level trade credit model with shortage for deteriorating products using hybrid metaheuristic algorithm
Published 2015“…In order to evaluate the solutions of the hybrid algorithm, the models are also solved by a global optimization solver,Branch-And-Reduce Optimization Navigator (BARON). …”
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Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems
Published 2024“…A case study conducted with USIM Tamhidi programs to evaluate the Hybrid-IWD algorithm has produced a successful Tamhidi exam timetable in comparison with manual approach.…”
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Moreover, the third test used ten natural domain datasets obtained from UCI Repository, in about fifteen different experiments, using three to four different Machine Learning Algorithms for performance evaluation. …”
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Profit Optimization of a Refrigerated Gas Plant
Published 2007“…This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. …”
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Profit Optimization of a Refrigerated Gas Plant
Published 2007“…This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. …”
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Profit Optimization of a Refrigerated Gas Plant
Published 2007“…This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. …”
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An evolutionary based features construction methods for data summarization approach
Published 2015“…In the process of summarizing relational data, a genetic algorithm is also applied and several feature scoring measures are evaluated in order to find the best set of relevant constructed features. …”
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Maximum 2-satisfiability in radial basis function neural network
Published 2020“…Correctly, this logic plays a prominent role in numerous applications as a combinatorial optimization logic. MAX2SAT is a case of MAX-kSAT and is written in Conjunctive Normal Form (CNF) with two variables in each clause. …”
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DRIFT ANALYSIS ON NEURAL NETWORK MODEL OF HEAT EXCHANGER FOULING
Published 2008“…Information Criteria have been reported to be used for the selection of relevant input variables and determination of optimal NN model structures. …”
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients
Published 2017“…Based on the location of the lung, the liver dome is automatically detected and the liver is then extracted by random walkers method and refined using a fuzzy level set method. This is followed by the clustering of the liver tissues using particle swarm optimized spatial FCM algorithm. …”
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Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions
Published 2023“…Results demonstrate that ARIMA outperforms the other models in all cases, accurately projecting the price variability within the actual price range. …”
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Capacity planning for mixed-load tester under demand and testing time uncertainty
Published 2018“…Currently,the company’s issue is low tester utilization of about 71%,well below the target of 96%.The objective of this research is to improve tester utilization while achieving the production target under uncertain demand and testing time and also to determine the break-even point on the testers required.A novel approach of integrating a mathematical model,robust optimization model,genetic algorithm,simulation model and cost–volume –profit analysis was developed.Firstly,a mathematical model of mixed-load tester was formulated.Next,a set of discrete scenarios was proposed to address uncertain demand and testing time.A robust optimization and genetic algorithm model was developed to optimize the number of testers under the described uncertainties.Next,these scenarios were simulated using the Pro Model simulation software to validate the proposed models and to evaluate throughput and tester utilization.Finally,the cost–volume–profit analysis was performed for scenarios that require additional testers at various levels of uncertainties.The results showed that the proposed solution improved tester utilization by 25% compared to the current system.This research has contribution by developing novel hybrid methodology and able to provide useful insights to assist company’s managers to plan and allocate resources according to variations in customers’ demands and testing time.…”
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